As of 2022, South Africa's population increased and counted approximately 60.6 million inhabitants in total, of which the majority (roughly 49.1 million) were Black Africans. Individuals with an Indian or Asian background formed the smallest population group, counting approximately 1.56 million people overall. Looking at the population from a regional perspective, Gauteng (includes Johannesburg) is the smallest province of South Africa, though highly urbanized with a population of nearly 16 million people.

Increase in number of households

The total number of households increased annually between 2002 and 2022. Between this period, the number of households in South Africa grew by approximately 65 percent. Furthermore, households comprising two to three members were more common in urban areas (39.2 percent) than they were in rural areas (30.6 percent). Households with six or more people, on the other hand, amounted to 19.3 percent in rural areas, being roughly twice as common as those in urban areas.

Main sources of income

The majority of the households in South Africa had salaries or grants as a main source of income in 2019. Roughly 10.7 million drew their income from regular wages, whereas 7.9 million households received social grants paid by the government for citizens in need of state support.

As of 2023, South Africa's population increased and counted approximately 62.3 million inhabitants in total, of which the majority inhabited Gauteng, KwaZulu-Natal, and the Western-Eastern Cape. Gauteng (includes Johannesburg) is the smallest province in South Africa, though highly urbanized with a population of over 16 million people according to the estimates. Cape Town, on the other hand, is the largest city in South Africa with nearly 3.43 million inhabitants in the same year, whereas Durban counted 3.12 million citizens. However, looking at cities including municipalities, Johannesburg ranks first. High rate of young population South Africa has a substantial population of young people. In 2024, approximately 34.3 percent of the people were aged 19 years or younger. Those aged 60 or older, on the other hand, made-up over 10 percent of the total population. Distributing South African citizens by marital status, approximately half of the males and females were classified as single in 2021. Furthermore, 29.1 percent of the men were registered as married, whereas nearly 27 percent of the women walked down the aisle. Youth unemployment Youth unemployment fluctuated heavily between 2003 and 2022. In 2003, the unemployment rate stood at 36 percent, followed by a significant increase to 45.5 percent in 2010. However, it fluctuated again and as of 2022, over 51 percent of the youth were registered as unemployed. Furthermore, based on a survey conducted on the worries of South Africans, some 64 percent reported being worried about employment and the job market situation.

Geographic coverage

The 1985 census covered the so-called white areas of South Africa, i.e. the areas in the former four provinces of the Cape, the Orange Free State, Transvaal, and Natal. It also covered the so-called National States of KwaZulu, Kangwane, Gazankulu, Lebowa, Qwaqwa, and Kwandebele. The 1985 South African census excluded the areas of the Transkei, Bophutatswana, Ciskei, and Venda.

The 1985 Census dataset contains 9 data files. These refer to Development Regions demarcated by the South African Government according to their socio-economic conditions and development needs. These Development Regions are labeled A to J (there is no Region I, presumably because Statistics SA felt an "I" could be confused with the number 1). The 9 data files in the 1985 Census dataset refer to the following areas:

DEV REGION AREA COVERED A Western Cape Province including Walvis Bay B Northern Cape C Orange Free State and Qwaqwa D Eastern Cape/Border E Natal and Kwazulu F Eastern Transvaal, KaNgwane and part of the Simdlangentsha district of Kwazulu G Northern Transvaal, Lebowa and Gazankulu H PWV area, Moutse and KwaNdebele J Western Transvaal

Analysis unit

The units of analysis under observation in the South African census 1985 are households and individuals

Universe

The South African census 1985 census covered the provinces of the Cape, the Orange Free State, Transvaal, and Nata and the so-called National States of KwaZulu, Kangwane, Gazankulu, Lebowa, Qwaqwa, and Kwandebele. The 1985 South African census excluded the areas of the Transkei, Bophutatswana, Ciskei, and Venda.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Although the census was meant to cover all residents of the so called white areas of South Africa, in 88 areas door-to-door surveys were not possible and the population in these areas was enumerated by means of a sample survey conducted by the Human Sciences Research Council.

Mode of data collection

Face-to-face [f2f]

Research instrument

The1985 population census questionnaire was administered to each household and collected information on household and area type, and information on household members, including relationship within household, sex, age, marital status, population group, birthplace, country of citizenship, level of education, occupation, identity of employer and the nature of economic activities

Data appraisal

UNDER-ENUMERATION: The following under-enumeration figures have been calculated for the 1985 census. Estimated percentage distribution of undercount by race according to the HSRC: Percent undercount
Whites 7.6%
Blacks in the “RSA” 20.4% Blacks in the “National States” 15.1% Coloureds 1.0% Asians 4.6%

As of 2024, around 13.2 million people in South Africa are living in extreme poverty, with the poverty threshold at 2.15 U.S. dollars daily. This means that 139,563 more people were pushed into poverty compared to 2023. Moreover, the headcount was forecast to increase in the coming years. By 2030, over 13.4 million South Africans will live on a maximum of 2.15 U.S. dollars per day. Who is considered poor domestically? Poverty is measured using several matrices. For example, local authorities tend to rely on the national poverty line, assessed based on consumer price indices (CPI) of a basket of goods of food and non-food components. In 2023, the domestic poverty line in South Africa stood at 1,109 South African rand per month (around 62.14 U.S. dollars per month). According to a survey, social inequality and poverty worried a significant share of the South African respondents. As of September 2024, some 33 percent of the respondents reported that they were worried about the state of poverty and unequal income distribution in the country.   Eastern Cape residents received more grants South Africa’s labor market has struggled to absorb the country’s population. In 2023, almost a third of the economically active population was unemployed. Local authorities employ relief assistance and social grants in an attempt to reduce poverty and assist poor individuals. In 2023, almost 50 percent of South African households received state support, with the majority share benefiting in the Eastern Cape.

Abstract

The Afrobarometer is a comparative series of public attitude surveys that assess African citizen's attitudes to democracy and governance, markets, and civil society, among other topics. The surveys have been undertaken at periodic intervals since 1999. The Afrobarometer's coverage has increased over time. Round 1 (1999-2001) initially covered 7 countries and was later extended to 12 countries. Round 2 (2002-2004) surveyed citizens in 16 countries. Round 3 (2005-2006) 18 countries, Round 4 (2008) 20 countries, Round 5 (2011-2013) 34 countries, Round 6 (2014-2015) 36 countries, and Round 7 (2016-2018) 34 countries. The survey covered 34 countries in Round 8 (2019-2021).

Geographic coverage

National coverage

Analysis unit

Individual

Universe

Citizens of South Africa who are 18 years and older

Kind of data

Sample survey data [ssd]

Sampling procedure

Afrobarometer uses national probability samples designed to meet the following criteria. Samples are designed to generate a sample that is a representative cross-section of all citizens of voting age in a given country. The goal is to give every adult citizen an equal and known chance of being selected for an interview. They achieve this by:

• using random selection methods at every stage of sampling; • sampling at all stages with probability proportionate to population size wherever possible to ensure that larger (i.e., more populated) geographic units have a proportionally greater probability of being chosen into the sample.

The sampling universe normally includes all citizens age 18 and older. As a standard practice, we exclude people living in institutionalized settings, such as students in dormitories, patients in hospitals, and persons in prisons or nursing homes. Occasionally, we must also exclude people living in areas determined to be inaccessible due to conflict or insecurity. Any such exclusion is noted in the technical information report (TIR) that accompanies each data set.

Sample size and design Samples usually include either 1,200 or 2,400 cases. A randomly selected sample of n=1200 cases allows inferences to national adult populations with a margin of sampling error of no more than +/-2.8% with a confidence level of 95 percent. With a sample size of n=2400, the margin of error decreases to +/-2.0% at 95 percent confidence level.

The sample design is a clustered, stratified, multi-stage, area probability sample. Specifically, we first stratify the sample according to the main sub-national unit of government (state, province, region, etc.) and by urban or rural location.

Area stratification reduces the likelihood that distinctive ethnic or language groups are left out of the sample. Afrobarometer occasionally purposely oversamples certain populations that are politically significant within a country to ensure that the size of the sub-sample is large enough to be analysed. Any oversamples is noted in the TIR.

Sample stages Samples are drawn in either four or five stages:

Stage 1: In rural areas only, the first stage is to draw secondary sampling units (SSUs). SSUs are not used in urban areas, and in some countries they are not used in rural areas. See the TIR that accompanies each data set for specific details on the sample in any given country. Stage 2: We randomly select primary sampling units (PSU). Stage 3: We then randomly select sampling start points. Stage 4: Interviewers then randomly select households. Stage 5: Within the household, the interviewer randomly selects an individual respondent. Each interviewer alternates in each household between interviewing a man and interviewing a woman to ensure gender balance in the sample.

To keep the costs and logistics of fieldwork within manageable limits, eight interviews are clustered within each selected PSU.

South Africa - Sample size: 1,600 - Sampling Frame: The 2011 Population and Housing Census frame, from Statistics South Africa (Stats SA), was used to select individual PSUs. The allocation was based on the estimate of the national adult population from the 2016 Community Survey. - Sample design: Nationally representative, random, clustered, stratified, multi-stage area probability sample - Stratification: Region and rural-urban location - Stages: PSUs (from strata), start points, households, respondents - PSU selection: Probability Proportionate to Population Size (PPPS) - Cluster size: 4 households per PSU - Household selection: Randomly selected start points, followed by walk pattern using 5/10 interval - Respondent selection: Gender quota filled by alternating interviews between men and women; respondents of appropriate gender listed, after which computer randomly selects individual to be interviewed

Mode of data collection

Face-to-face [f2f]

Research instrument

The Round 8 questionnaire has been developed by the Questionnaire Committee after reviewing the findings and feedback obtained in previous Rounds, and securing input on preferred new topics from a host of donors, analysts, and users of the data.

The questionnaire consists of three parts: 1. Part 1 captures the steps for selecting households and respondents, and includes the introduction to the respondent and (pp.1-4). This section should be filled in by the Fieldworker. 2. Part 2 covers the core attitudinal and demographic questions that are asked by the Fieldworker and answered by the Respondent (Q1 – Q100). 3. Part 3 includes contextual questions about the setting and atmosphere of the interview, and collects information on the Fieldworker. This section is completed by the Fieldworker (Q101 – Q123).

Response rate

Outcome rates: - Contact rate: 86% - Cooperation rate: 60% - Refusal rate: 16% - Response rate: 51%

Sampling error estimates

The sample size yields country-level results with a margin of error of +/-2.5 percentage points at a 95% confidence level.

In 2020, cumulative South African emigrants amounted to roughly 915,000. The vast majority settled in the United Kingdom (around 247,000), followed by Australia (nearly 200,000). Together, the two countries constituted roughly 49 percent of the total South African migrants living abroad. Moreover, the third major country of destination for South Africans was the United States, with about 117,000 people living there. Overall, the 21 countries presented covered 94.4 percent of all South African migrants.

Language: a primary driver of emigration destinations

Language is a factor that helps ease communication and integration for individuals within a new society. Noticeably, the five leading destinations for South African emigrants had English as an official language. In South Africa, English was the second most spoken language outside households. Furthermore, the Netherlands ranked seventh, which language can also justify. Afrikaans, a language developed from 17th-century Dutch, was the third most spoken language among households in South Africa.

Unemployment a major worry and prevalent among youth    

A real worry for South Africans in 2022 was unemployment. As of April 2022, 64 percent of the respondents of a survey reported concern regarding the job market and the unemployment situation in the country. As of the first quarter of 2022, the unemployment rate among the age groups 15-24 years and 25-34 years was significantly higher than the rest, reaching 63.9 percent and 42.1 percent, respectively.

Chart and table of South Africa population from 1950 to 2025. United Nations projections are also included through the year 2100.

Poverty headcount ratio at $5.50 a day is the percentage of the population living on less than $5.50 a day at 2011 international prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.

Abstract

Every person, household and institution present in South Africa on Census Night, 9-10 October 1996, should have been enumerated in Census '96. The intent was to provide a count of all persons present within the territory of the Republic of South Africa at that time. More specifically, the purpose of this census was to collect, process and disseminate detailed statistics on population size, composition and distribution at a small area level. The 1996 South African population Census contains data collected on HOUSEHOLDS and INSTITUTIONS: dwellling type, home ownership, household assets, access to services and energy sources; INDIVIDUALS: age, population group, language, religion, citizenship, migration, fertility, mortality and disability; and economic characteristics of individuals, including employment activities and unemployment.

Geographic coverage

The South African Census 1996 has national coverage.

Analysis unit

The units of analysis for the South Africa Census 1996 were households, individuals and institutions

Universe

The South African Census 1996 covered every person present in South Africa on Census Night, 9-10 October 1996 (except foreign diplomats and their families).

Kind of data

Census/enumeration data [cen]

Sampling procedure

The data in the South African Census 1996 data file is a 10% unit level sample drawn from Census 1996 as follows:

1) Households: • A 10% sample of all households (excluding special institutions and hostels)

2) Persons: • A 10% sample of all persons as enumerated in the 1996 Population Census in South Africa

The census household records were explicitly stratified according to province and district council. Within each district council the records were further implicitly stratified by local authority. Within each implicit stratum the household records were ordered according to the unique seven-digit census enumerator area number, of which the first three digits are the (old) magisterial district number.

Mode of data collection

Face-to-face [f2f]

Research instrument

Different methods of enumeration were used to accommodate different situations and a variety of questionnaires were used. The information collected with each questionnaire differed slightly. The questionnaires used were as follows:

Questionnaire 1: (Household and personal questionnaire) This questionnaire was used in private households and within hostels which provided family accommodation. It contained 50 questions for each person and 15 for each household. Every household living in a private dwelling should have been enumerated on a household questionnaire. This questionnaire obtained information about the household and about each person who was present in the household on census night.

Questionnaire 2: (Summary book for hostels) This questionnaire was used to list all persons/households in the hostel and included 9 questions about the hostel. A summary book for hostels should have been completed for each hostel (that is, a compound for workers provided by mines, other employers, municipalities or local authorities). This questionnaire obtained information about the hostel and also listed all household and/or persons enumerated in the hostel. Some hostels contain people living in family groups. Where people were living as a household in a hostel, they were enumerated as such on a household questionnaire (which obtained information about the household and about each person who was present in the household on Census Night). On the final census file, they will be listed as for any other household and not as part of a hostel. Generally, hostels accommodate mostly individual workers. In these situations, persons were enumerated on separate personal questionnaires. These questionnaires obtained the same information on each person as would have been obtained on the household questionnaire. The persons will appear on the census file as part of a hostel. Some hostels were enumerated as special institutions and not on the questionnaires designed specifically for hostels.

Questionnaire 3: (Enumerator's book for special enumeration) This questionnaire was used to obtain very basic information for individuals within institutions such as hotels, prisons, hospitals etc. as well as for homeless persons. Only 6 questions were asked of these people. The questionnaire also included 9 questions about the institution. An enumerator's book for special enumeration should have been completed for each institution such as prisons and hospitals. This questionnaire obtained information on the institution and listed all persons present. Each person was asked a brief sub-set of questions - just 7 compared to around 50 on the household and personal questionnaires. People in institutions could not be enumerated as households. Homeless persons were enumerated during a sweep on census night using a special questionnaire. The results were later transcribed to standard enumerator's books for special enumeration to facilitate coding and data entry.

Response rate

The final calculation of the undercount of persons, based on analysis of a post-enumeration survey (PES) conducted shortly after the original census, was performed by Statistics South Africa. The estimated reponse rates are detailed below, both according to stratum and for the country as a whole. An estimated 10,7% of the people in South Africa, through the course of the census process, were not enumerated. For more information on the undercount and PES, see the publication, "Calculating the Undercount in Census '96", Statistics South Africa Report No. 03-01-18 (1996) which is included in the external documents section.

Undercount of persons by province (stratum, in %):

Western Cape 8,69
Eastern Cape 10,57
Northern Cape 15,59
Free State 8,75
KwaZulu-Natal 12,81
North West 9,37
Gauteng 9,99
Mpumalanga 10,09
Northern Province 11,28

South Africa 10,69

Abstract

The 1998 South Africa Demographic and Health Survey (SADHS) is the first study of its kind to be conducted in South Africa and heralds a new era of reliable and relevant information in South Africa. The SADHS, a nation-wide survey has collected information on key maternal and child health indicators, and in a first for international demographic and health surveys, the South African survey contains data on the health and disease patterns in adults.

Plans to conduct the South Africa Demographic and Health Survey go as far back as 1995, when the Department of Health National Health Information Systems of South Africa (NHIS/SA) committee, recognised serious gaps in information required for health service planning and monitoring.

Fieldwork was conducted between late January and September 1998, during which time 12,247 households were visited, 17,500 people throughout nine provinces were interviewed and 175 interviewers were trained to interview in 11 languages.

The aim of the 1998 South Africa Demographic and Health Survey (SADHS) was to collect data as part of the National Health Information System of South Africa (NHIS/SA). The survey results are intended to assist policymakers and programme managers in evaluating and designing programmes and strategies for improving health services in the country. A variety of demographic and health indicators were collected in order to achieve the following general objectives:

(i) To contribute to the information base for health and population development programme management through accurate and timely data on a range of demographic and health indicators. (ii) To provide baseline data for monitoring programmes and future planning. (iii) To build research and research management capacity in large-scale national demographic and health surveys.

The primary objective of the SADHS is to provide up-to-date information on: - basic demographic rates, particularly fertility and childhood mortality levels, - awareness and use of contraceptive methods, - breastfeeding practices, - maternal and child health, - awareness of HIV/AIDS, - chronic health conditions among adults, - lifestyles that affect the health status of adults, and - anthropometric indicators.

Geographic coverage

It was designed principally to produce reliable estimates of demographic rates (particularly fertility and childhood mortality rates), of maternal and child health indicators, and of contraceptive knowledge and use for the country as a whole, the urban and the non-urban areas separately, and for the nine provinces.

Analysis unit

• Household
• Women age 15-49
• Men age 15 and above

Universe

The 1998 South African Demographic and Health Survey (SADHS) covered the population living in private households in the country.

Kind of data

Sample survey data

Sampling procedure

The 1998 South African Demographic and Health Survey (SADHS) covered the population living in private households in the country. The design for the SADHS called for a representative probability sample of approximately 12,000 completed individual interviews with women between the ages of 15 and 49. It was designed principally to produce reliable estimates of demographic rates (particularly fertility and childhood mortality rates), of maternal and child health indicators, and of contraceptive knowledge and use for the country as a whole, the urban and the non-urban areas separately, and for the nine provinces. As far as possible, estimates were to be produced for the four South African population groups. Also, in the Eastern Cape province, estimates of selected indicators were required for each of the five health regions.

In addition to the main survey of households and women 15-49 that followed the DHS model, an adult health module was administered to a sample of adults aged 15 and over in half of the households selected for the main survey. The adult health module collected information on oral health, occupational hazard and chronic diseases of lifestyle.

SAMPLING FRAME

The sampling frame for the SADHS was the list of approximately 86,000 enumeration areas (EAs) created by Central Statistics (now Statistics South Africa, SSA) for the Census conducted in October 1996. The EAs, ranged from about 100 to 250 households, and were stratified by province, urban and non-urban residence and by EA type. The number of households in the EA served as a measure of size of the EA.

CHARACTERISTICS OF THE SADHS SAMPLE

The sample for the SADHS was selected in two stages. Due to confidentiality of the census data, the sampling was carried out by experts at the CSS according to specifications developed by members of the SADHS team. Within each stratum a two stage sample was selected. The primary sampling units (PSUs), corresponded to the EAs and will be selected with probability proportional to size (PPS), the size being the number of households residing in the EA, or where this was not available, the number of census visiting points in the EA. This led to 972 PSUs being selected for the SADHS (690 in urban areas and 282 in non-urban areas. Where provided by SSA, the lists of visiting points together with the households found in these visiting points, or alternatively a map of the EA which showed the households, was used as the frame for second-stage sampling to select the households to be visited by the SADHS interviewing teams during the main survey fieldwork. This sampling was carried out by the MRC behalf of the SADHS working group. If a list of visiting points or a map was not available from SSA, then the survey team took a systematic sample of visiting points in the field. In an urban EA ten visiting points were sampled, while in a non-urban EA twenty visiting points were sampled. The survey team then interviewed the household in the selected visiting point. If there were two households in the selected visiting point, both households were interviewed. If there were three or more households, then the team randomly selected one household for interview. In each selected household, a household questionnaire was administered; all women between the ages of 15 and 49 were identified and interviewed with a woman questionnaire. In half of the selected households (identified by the SADHS working group), all adults over 15 years of age were also identified and interviewed with an adult health questionnaire.

SAMPLE ALLOCATION

Except for Eastern Cape, the provinces were stratified by urban and non-urban areas, for a total of 16 sampling strata. Eastern Cape was stratified by the five health regions and urban and non-urban within each region, for a total of 10 sampling strata. There were thus 26 strata in total.

Originally, it was decided that a sample of 9,000 women 15-49 with complete interviews allocated equally to the nine provinces would be adequate to provide estimates for each province separately; results of other demographic and health surveys have shown that a minimum sample of 1,000 women is required in order to obtain estimates of fertility and childhood mortality rates at an acceptable level of sampling errors. Since one of the objectives of the SADHS was to also provide separate estimates for each of the four population groups, this allocation of 1,000 women per province would not provide enough cases for the Asian population group since they represent only 2.6 percent of the population (according to the results of the 1994 October Household Survey conducted by SSA). The decision was taken to add an additional sample of 1,000 women to the urban areas of KwaZulu-Natal and Gauteng to try to capture as many Asian women as possible as Asians are found mostly in these areas. A more specific sampling scheme to obtain an exact number of Asian women was not possible for two reasons: the population distribution by population group was not yet available from the 1996 census and the sampling frame of EAs cannot be stratified by population group according to SSA as the old system of identifying EAs by population group has been abolished.

An additional sample of 2,000 women was added to Eastern Cape at the request of the Eastern Cape province who funded this additional sample. In Eastern Cape, results by urban and non-urban areas can be given. Results of selected indicators such as contraceptive knowledge and use can also be produced separately for each of the five health regions but not for urban/non-urban within health region.

Result shows the allocation of the target sample of 12,000 women by province and by urban/nonurban residence. Within each province, the sample is allocated proportionately to the urban/non-urban areas.

In the above allocation, the urban areas of KwaZulu-Natal have been oversampled by about 57 percent while those of Gauteng have been oversampled by less than 1 percent. For comparison purposes, it shows a proportional allocation of the 12,000 women to the nine provinces that would result in a completely self-weighting sample but does not allow for reliable estimates for at least four provinces (Northern Cape, Free State, Mpumalanga and North-West).

The number of households to be selected for each stratum was calculated as follows:

• According to the 1994 October Household Survey, the estimated number of women 15-49 per households is 1.2. The overall response rate was assumed to be 80 percent, i.e., of the households selected for the survey only 90 percent would be successfully interviewed, and of the women identified in the households with completed interviews, only 90 percent would have a complete woman questionnaire. Using these two parameters in the above equation, we would expect to select approximately 12,500 households in order to yield the target sample of women.

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Unemployment Rate in South Africa decreased to 31.90 percent in the fourth quarter of 2024 from 32.10 percent in the third quarter of 2024. This dataset provides - South Africa Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Abstract

The population census conducted in South Africa in 1985 covered the whole of South Africa, but excluded the "Homelands" of Transkei, Bophutatswana, Ciskei, and Venda. This dataset is the full census, as opposed to the 10% sample datasets provided by Statistics South Africa from 1996 onwards.

Geographic coverage

The 1985 census covered the so-called white areas of South Africa - the provinces of the Cape, the Orange Free State, Transvaal, and Natal - and the so-called National States of KwaZulu, Kangwane, Gazankulu, Lebowa, Qwaqwa, and Kwandebele. The 1985 South African census excluded the areas of the Transkei, Bophutatswana, Ciskei, and Venda.

The 1985 Census dataset has 9 data files. These refer to Development Regions demarcated by the South African Government according to their socio-economic conditions and development needs. These Development Regions are labeled A to J (there is no Region I, presumably because Statistics SA felt an "I" could be confused with the number 1). The 9 data files in the 1985 Census dataset refer to the following areas:

DEV REGION AREA COVERED A Western Cape Province including Walvis Bay B Northern Cape C Orange Free State and Qwaqwa D Eastern Cape/Border E Natal and Kwazulu F Eastern Transvaal, KaNgwane and part of the Simdlangentsha district of Kwazulu G Northern Transvaal, Lebowa and Gazankulu H PWV area, Moutse and KwaNdebele J Western Transvaal

Analysis unit

The units of analysis under observation in the South African census 1985 are households and individuals

Universe

All persons who were present on Republic of South African territory during census night were enumerated. Visitors from abroad who were present in the RSA on holiday or business on the night of the census, as well as foreigners (and their families) who were studying or economically active, were enumerated but not included in the final data. Likewise, members of the Diplomatic and Consular Corps of foreign countries were not included. However, the South African personnel linked to the foreign missions including domestic workers were enumerated. Crews and passengers of ships were also not enumerated, unless they were normally resident in the Republic of South Africa. Residents of the RSA who were absent from the night were as far as possible enumerated on their return and included in the region where they normally resided. Personnel of the South African Government stationed abroad and their families were, however enumerated. Such persons were included in the Transvaal (Pretoria).

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

The1985 population census questionnaire was administered to each household and collected information on household and area type, and information on household members, including relationship within household, sex, age, marital status, population group, birthplace, country of citizenship, level of education, occupation, identity of employer and the nature of economic activities

Data appraisal

UNDER-ENUMERATION: The following under-enumeration figures have been calculated for the 1985 census. Estimated percentage distribution of undercount by race according to the HSRC: Percent undercount
Whites 7.6%
Blacks in the “RSA” 20.4% Blacks in the “National States” 15.1% Coloureds 1.0% Asians 4.6%

There were almost 700 thousand slaves in the US in 1790, which equated to approximately 18 percent of the total population, or roughly one in every six people. By 1860, the final census taken before the American Civil War, there were four million slaves in the South, compared with less than 0.5 million free African Americans in all of the US. Of the 4.4 million African Americans in the US before the war, almost four million of these people were held as slaves; meaning that for all African Americans living in the US in 1860, there was an 89 percent* chance that they lived in slavery. A brief history Trans-Atlantic slavery began in the early sixteenth century, when the Portuguese and Spanish forcefully brought captured African slaves to the New World, in order to work for them. The British Empire introduced slavery to North America on a large scale, and the economy of the British colonies there depended on slave labor, particularly regarding cotton, sugar and tobacco output. In the seventeenth and eighteenth century the number of slaves being brought to the Americas increased exponentially, and at the time of American independence it was legal in all thirteen colonies. Although slavery became increasingly prohibited in the north, the number of slaves remained high during this time as they were simply relocated or sold from the north to the south. It is also important to remember that the children of slaves were also viewed as property, and (apart from some very rare cases) were born into a life of slavery. Abolition and the American Civil War In the years that followed independence, the Northern States began gradually prohibiting slavery, and it was officially abolished there by 1805, and the importation of slave labor was prohibited nationwide from 1808 (although both still existed in practice after this). Business owners in the Southern States however depended on slave labor in order to meet the demand of their rapidly expanding industries, and the issue of slavery continued to polarize American society in the decades to come. This culminated in the election of President Abraham Lincoln in 1860, who promised to prohibit slavery in the newly acquired territories to the west, leading to the American Civil War from 1861 to 1865. Although the Confederacy (south) were victorious in much of the early stages of the war, the strength in numbers of the northern states (including many free, black men), eventually resulted in a victory for the Union (north), and the nationwide abolishment of slavery with the Thirteenth Amendment in 1865. Legacy In total, an estimated twelve to thirteen million Africans were transported to the Americas as slaves, and this does not include the high number who did not survive the journey (which was as high as 23 percent in some years). In the 150 years since the abolishment of slavery in the US, the African-American community have continuously campaigned for equal rights and opportunities that were not afforded to them along with freedom. The most prominent themes have been the Civil Rights Movement, voter suppression, mass incarceration and the relationship between the police and the African-American community has taken the spotlight in recent years.

Abstract

Round 1 of the Afrobarometer survey was conducted from July 1999 through June 2001 in 12 African countries, to solicit public opinion on democracy, governance, markets, and national identity. The full 12 country dataset released was pieced together out of different projects, Round 1 of the Afrobarometer survey,the old Southern African Democracy Barometer, and similar surveys done in West and East Africa.

The 7 country dataset is a subset of the Round 1 survey dataset, and consists of a combined dataset for the 7 Southern African countries surveyed with other African countries in Round 1, 1999-2000 (Botswana, Lesotho, Malawi, Namibia, South Africa, Zambia and Zimbabwe). It is a useful dataset because, in contrast to the full 12 country Round 1 dataset, all countries in this dataset were surveyed with the identical questionnaire

Geographic coverage

Botswana Lesotho Malawi Namibia South Africa Zambia Zimbabwe

Analysis unit

Basic units of analysis that the study investigates include: individuals and groups

Kind of data

Sample survey data [ssd]

Sampling procedure

A new sample has to be drawn for each round of Afrobarometer surveys. Whereas the standard sample size for Round 3 surveys will be 1200 cases, a larger sample size will be required in societies that are extremely heterogeneous (such as South Africa and Nigeria), where the sample size will be increased to 2400. Other adaptations may be necessary within some countries to account for the varying quality of the census data or the availability of census maps.

The sample is designed as a representative cross-section of all citizens of voting age in a given country. The goal is to give every adult citizen an equal and known chance of selection for interview. We strive to reach this objective by (a) strictly applying random selection methods at every stage of sampling and by (b) applying sampling with probability proportionate to population size wherever possible. A randomly selected sample of 1200 cases allows inferences to national adult populations with a margin of sampling error of no more than plus or minus 2.5 percent with a confidence level of 95 percent. If the sample size is increased to 2400, the confidence interval shrinks to plus or minus 2 percent.

Sample Universe

The sample universe for Afrobarometer surveys includes all citizens of voting age within the country. In other words, we exclude anyone who is not a citizen and anyone who has not attained this age (usually 18 years) on the day of the survey. Also excluded are areas determined to be either inaccessible or not relevant to the study, such as those experiencing armed conflict or natural disasters, as well as national parks and game reserves. As a matter of practice, we have also excluded people living in institutionalized settings, such as students in dormitories and persons in prisons or nursing homes.

What to do about areas experiencing political unrest? On the one hand we want to include them because they are politically important. On the other hand, we want to avoid stretching out the fieldwork over many months while we wait for the situation to settle down. It was agreed at the 2002 Cape Town Planning Workshop that it is difficult to come up with a general rule that will fit all imaginable circumstances. We will therefore make judgments on a case-by-case basis on whether or not to proceed with fieldwork or to exclude or substitute areas of conflict. National Partners are requested to consult Core Partners on any major delays, exclusions or substitutions of this sort.

Sample Design

The sample design is a clustered, stratified, multi-stage, area probability sample.

To repeat the main sampling principle, the objective of the design is to give every sample element (i.e. adult citizen) an equal and known chance of being chosen for inclusion in the sample. We strive to reach this objective by (a) strictly applying random selection methods at every stage of sampling and by (b) applying sampling with probability proportionate to population size wherever possible.

In a series of stages, geographically defined sampling units of decreasing size are selected. To ensure that the sample is representative, the probability of selection at various stages is adjusted as follows:

The sample is stratified by key social characteristics in the population such as sub-national area (e.g. region/province) and residential locality (urban or rural). The area stratification reduces the likelihood that distinctive ethnic or language groups are left out of the sample. And the urban/rural stratification is a means to make sure that these localities are represented in their correct proportions. Wherever possible, and always in the first stage of sampling, random sampling is conducted with probability proportionate to population size (PPPS). The purpose is to guarantee that larger (i.e., more populated) geographical units have a proportionally greater probability of being chosen into the sample. The sampling design has four stages

A first-stage to stratify and randomly select primary sampling units;

A second-stage to randomly select sampling start-points;

A third stage to randomly choose households;

A final-stage involving the random selection of individual respondents

We shall deal with each of these stages in turn.

STAGE ONE: Selection of Primary Sampling Units (PSUs)

The primary sampling units (PSU's) are the smallest, well-defined geographic units for which reliable population data are available. In most countries, these will be Census Enumeration Areas (or EAs). Most national census data and maps are broken down to the EA level. In the text that follows we will use the acronyms PSU and EA interchangeably because, when census data are employed, they refer to the same unit.

We strongly recommend that NIs use official national census data as the sampling frame for Afrobarometer surveys. Where recent or reliable census data are not available, NIs are asked to inform the relevant Core Partner before they substitute any other demographic data. Where the census is out of date, NIs should consult a demographer to obtain the best possible estimates of population growth rates. These should be applied to the outdated census data in order to make projections of population figures for the year of the survey. It is important to bear in mind that population growth rates vary by area (region) and (especially) between rural and urban localities. Therefore, any projected census data should include adjustments to take such variations into account.

Indeed, we urge NIs to establish collegial working relationships within professionals in the national census bureau, not only to obtain the most recent census data, projections, and maps, but to gain access to sampling expertise. NIs may even commission a census statistician to draw the sample to Afrobarometer specifications, provided that provision for this service has been made in the survey budget.

Regardless of who draws the sample, the NIs should thoroughly acquaint themselves with the strengths and weaknesses of the available census data and the availability and quality of EA maps. The country and methodology reports should cite the exact census data used, its known shortcomings, if any, and any projections made from the data. At minimum, the NI must know the size of the population and the urban/rural population divide in each region in order to specify how to distribute population and PSU's in the first stage of sampling. National investigators should obtain this written data before they attempt to stratify the sample.

Once this data is obtained, the sample population (either 1200 or 2400) should be stratified, first by area (region/province) and then by residential locality (urban or rural). In each case, the proportion of the sample in each locality in each region should be the same as its proportion in the national population as indicated by the updated census figures.

Having stratified the sample, it is then possible to determine how many PSU's should be selected for the country as a whole, for each region, and for each urban or rural locality.

The total number of PSU's to be selected for the whole country is determined by calculating the maximum degree of clustering of interviews one can accept in any PSU. Because PSUs (which are usually geographically small EAs) tend to be socially homogenous we do not want to select too many people in any one place. Thus, the Afrobarometer has established a standard of no more than 8 interviews per PSU. For a sample size of 1200, the sample must therefore contain 150 PSUs/EAs (1200 divided by 8). For a sample size of 2400, there must be 300 PSUs/EAs.

These PSUs should then be allocated proportionally to the urban and rural localities within each regional stratum of the sample. Let's take a couple of examples from a country with a sample size of 1200. If the urban locality of Region X in this country constitutes 10 percent of the current national population, then the sample for this stratum should be 15 PSUs (calculated as 10 percent of 150 PSUs). If the rural population of Region Y constitutes 4 percent of the current national population, then the sample for this stratum should be 6 PSU's.

The next step is to select particular PSUs/EAs using random methods. Using the above example of the rural localities in Region Y, let us say that you need to pick 6 sample EAs out of a census list that contains a total of 240 rural EAs in Region Y. But which 6? If the EAs created by the national census bureau are of equal or roughly equal population size, then selection is relatively straightforward. Just number all EAs consecutively, then make six selections using a table of random numbers. This procedure, known as simple random sampling (SRS), will

Abstract

The Afrobarometer South Africa Survey 2002 was part of Round 1 of the Afrobarometer surveys, and includes data on the attitudes and opinions of the citizens of South Africa. Respondents were asked to rate South African President Mbeki and his administrations' overall performance and to state the most important issue facing the nation. Opinions were gathered on the role of the government in improving the economy, whether corruption existed in local and national government, whether government officials were responsive to problems of the general population, and whether local government officials, the police, the courts, the overall criminal justice system, the South African Defense Force, the media, the Independent Electoral Commission, and the South African Broadcasting Corporation could be trusted. Respondents were polled on their knowledge of government officials, their level of personal involvement in political, governmental, and community affairs, the inclusiveness of the government, and what their reactions would be to executive branch-sponsored government-imposed restrictions or prohibitions on the media, the judicial system, and parliament.

Geographic coverage

The South African Afrobarometer Survey 2000 has national coverage.

Analysis unit

The units of analysis for the South African Afrobarometer 2000 were individuals and households

Universe

The survey universe is citizens of South Africa 18 years of age or older

Kind of data

Sample survey data [ssd]

Sampling procedure

The survey used a multi-stage, stratified, area cluster probability sample

Mode of data collection

Face-to-face [f2f]

Research instrument

There was one questionnaire for the Southern African Barometer Project Democracy Survey I (South Africa) conducted in 2000.

Economic questions addressed the past, present, and future of the country's and the respondent's economic condition, whether great income disparities are fair, and whether encouraging people to start small businesses would create more jobs.

Societal questions addressed how much trust could be placed in others, whether it is wise to plan ahead, whether everyone should be responsible for themselves and their own success or failure, what characteristics respondents used to identify themselves, whether it was easy to obtain assistance with securing food, water, schooling, and medical services, and by what methods respondents secured food, water, news, information, and medical services.

Background variables include age, home language, education, current employment status, employment history, family financial situation over the last 12 months, monetary support system, whether a close friend or relative had died from AIDS, language used in interview, sex, ethnicity, type of physical disability, if any, type of housing, location of interview and respondent's attitude during interview.

Response rate

The survey had a response rate of approximately 90 percent

The Gross Domestic Product (GDP) in South Africa expanded 0.60 percent in the fourth quarter of 2024 over the previous quarter. This dataset provides - South Africa GDP Growth Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

South Africa ZA: Contraceptive Prevalence: Any Methods: % of Women Aged 15-49 data was reported at 54.600 % in 2016. This records a decrease from the previous number of 59.900 % for 2003. South Africa ZA: Contraceptive Prevalence: Any Methods: % of Women Aged 15-49 data is updated yearly, averaging 55.450 % from Dec 1980 (Median) to 2016, with 6 observations. The data reached an all-time high of 59.900 % in 2003 and a record low of 48.000 % in 1980. South Africa ZA: Contraceptive Prevalence: Any Methods: % of Women Aged 15-49 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank: Health Statistics. Contraceptive prevalence rate is the percentage of women who are practicing, or whose sexual partners are practicing, any form of contraception. It is usually measured for women ages 15-49 who are married or in union.; ; UNICEF's State of the World's Children and Childinfo, United Nations Population Division's World Contraceptive Use, household surveys including Demographic and Health Surveys and Multiple Indicator Cluster Surveys.; Weighted average; Contraceptive prevalence amongst women of reproductive age is an indicator of women's empowerment and is related to maternal health, HIV/AIDS, and gender equality.

Abstract

The South Africa Demographic and Health Survey 2016 (SADHS 2016) is the third DHS conducted in South Africa and follows surveys carried out in 1998 and 2003. The SADHS 2016 was designed to provide up-to-date information on key indicators needed to track progress in South Africa’s health programmes.

Geographic coverage

The survey was designed to provide representative estimates for main demographic and health indicators for the country as a whole, for urban and non-urban areas separately, and for each of the nine provinces in South Africa: Western Cape, Eastern Cape, Northern Cape, Free State, KwaZulu-Natal, North West, Gauteng, Mpumalanga, and Limpopo.

Analysis unit

Households and individuals

Universe

The South African Demographic and Health Survey (SADHS) covered the population living in private households in the country.

Kind of data

Sample survey data

Sampling procedure

The sample for the SADHS 2016 is a stratified sample selected in two stages from the Master Sampling Frame. Stratification was achieved by separating each province into urban, traditional, and farm areas. In total, 26 sampling strata were created (since there are no traditional areas in Western Cape). Samples were selected independently in each sampling stratum by a two-stage selection. Implicit stratification and proportional allocation were achieved at each of the lower administrative levels within a given sampling stratum by sorting the sampling frame according to administrative units at different levels in each stratum and using probability proportional to size selection at the first stage of sampling.

Mode of data collection

Face-to-face [f2f]

Research instrument

Five questionnaires were used in the SADHS 2016. Interviewers used tablet computers to record responses during interviews.

Response rate

Of the total 972 PSUs that were selected, fieldwork was not implemented in three PSUs due to concerns about the safety of the interviewers and the questionnaires for another three PSUs were lost in transit. The data file contains information for a total of 966 PSUs. A total of 12,860 households was selected for the sample and 12,247 were successfully interviewed. The shortfall is primarily due to refusals and to dwellings that were vacant or in which the inhabitants had left for an extended period at the time they were visited by interviewing teams.

Of the 12,638 households occupied 97 percent were successfully interviewed. In these households, 12,327 women were identified as eligible for the individual women's interview (15-49) and interviews were completed with 11,735 or 95 percent of them. In the one half of the households that were selected for inclusion in the adult health survey 14,928 eligible adults age 15 and over were identified of which 13,827 or 93 percent were interviewed. The principal reason for non-response among eligible women and men was the failure to find them at home despite repeated visits to the household. The refusal rate was about 2 percent.

Sampling error estimates

Sampling errors are computed in SAS, using programs developed by ICF. These programs use the Taylor linearization method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

The number of visitors to the United States from South Africa increased by around 34 pecent from 2022 to 2023. In 2023, the number of travelers from South Africa reached 108,691, up from the previous year's total of 80,652.

Relative concentration of the Southern California region's Black/African American population. The variable BLACKALN records all individuals who select black or African American as their SOLE racial identity in response to the Census questionnaire, regardless of their response to the Hispanic ethnicity question. Both Hispanic and non-Hispanic in the Census questionnaire are potentially associated with black race alone. "Relative concentration" is a measure that compares the proportion of population within each Census block group data unit that identify as Black/African American alone to the proportion of all people that live within the 13,312 block groups in the Southern California RRK region that identify as Black/African American alone. Example: if 5.2% of people in a block group identify as BLACKALN, the block group has twice the proportion of BLACKALN individuals compared to the Southern California RRK region (2.6%), and more than three times the proportion compared to the entire state of California (1.6%). If the local proportion is twice the regional proportion, then BLACKALN individuals are highly concentrated locally.